• Title/Summary/Keyword: Comprehensive optimization

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Multi-objective optimization of printed circuit heat exchanger with airfoil fins based on the improved PSO-BP neural network and the NSGA-II algorithm

  • Jiabing Wang;Linlang Zeng;Kun Yang
    • Nuclear Engineering and Technology
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    • v.55 no.6
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    • pp.2125-2138
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    • 2023
  • The printed circuit heat exchanger (PCHE) with airfoil fins has the benefits of high compactness, high efficiency and superior heat transfer performance. A novel multi-objective optimization approach is presented to design the airfoil fin PCHE in this paper. Three optimization design variables (the vertical number, the horizontal number and the staggered number) are obtained by means of dimensionless airfoil fin arrangement parameters. And the optimization objective is to maximize the Nusselt number (Nu) and minimize the Fanning friction factor (f). Firstly, in order to investigate the impact of design variables on the thermal-hydraulic performance, a parametric study via the design of experiments is proposed. Subsequently, the relationships between three optimization design variables and two objective functions (Nu and f) are characterized by an improved particle swarm optimization-backpropagation artificial neural network. Finally, a multi-objective optimization is used to construct the Pareto optimal front, in which the non-dominated sorting genetic algorithm II is used. The comprehensive performance is found to be the best when the airfoil fins are completely staggered arrangement. And the best compromise solution based on the TOPSIS method is identified as the optimal solution, which can achieve the requirement of high heat transfer performance and low flow resistance.

Multi-objective BESO topology optimization for stiffness and frequency of continuum structures

  • Teimouri, Mohsen;Asgari, Masoud
    • Structural Engineering and Mechanics
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    • v.72 no.2
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    • pp.181-190
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    • 2019
  • Topology optimization of structures seeking the best distribution of mass in a design space to improve the structural performance and reduce the weight of a structure is one of the most comprehensive issues in the field of structural optimization. In addition to structures stiffness as the most common objective function, frequency optimization is of great importance in variety of applications too. In this paper, an efficient multi-objective Bi-directional Evolutionary Structural Optimization (BESO) method is developed for topology optimization of frequency and stiffness in continuum structures simultaneously. A software package including a Matlab code and Abaqus FE solver has been created for the numerical implementation of multi-objective BESO utilizing the weighted function method. At the same time, by considering the weaknesses of the optimized structure in single-objective optimizations for stiffness or frequency problems, slight modifications have been done on the numerical algorithm of developed multi-objective BESO in order to overcome challenges due to artificial localized modes, checker boarding and geometrical symmetry constraint during the progressive iterations of optimization. Numerical results show that the proposed Multiobjective BESO method is efficient and optimal solutions can be obtained for continuum structures based on an existent finite element model of the structures.

Efficiency Optimization Control of Induction Motor System using Fuzzy Control (퍼지제어를 이용한 유도전동기 시스템의 효율 최적화 제어)

  • Chung, Dong-Hwa;Park, Gi-Tae;Lee, Hong-Gyun
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.50 no.7
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    • pp.318-324
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    • 2001
  • Efficiency optimization of an indirect vector controlled induction motor drive is proposed. The loss models are used in the validation of the fuzzy logic based on-line efficiency optimization control. At steady state, the fuzzy controller adaptively changes the excitation current on the basis of measured input power, until the maximum efficiency point is reached. The pulsating torque, due to flux reduction, has been compensated by an ingenious feedforward scheme. During transient state, rated flux is established to get the best transient response. Through a comprehensive simulation study, the results confirmed the validity of the proposed method.

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Further Improvement in Rotor Aerodynamics Estimation in Helicopter Conceptual Design and Optimization Framework for a Compound Rotorcraft

  • Lim, JaeHoon;Shin, SangJoon;Kee, YoungJung
    • International Journal of Aeronautical and Space Sciences
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    • v.18 no.4
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    • pp.641-650
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    • 2017
  • In order to include the design capability for a compound rotorcraft in a helicopter conceptual design and optimization framework, relevant further improvement was planned and conducted. Previously, a certain conceptual design optimization framework was developed by the present authors to design a modern rotorcraft with single main and tail rotor. The previously developed framework was further improved to expand its capability for a compound rotorcraft. Specifically, its power estimation algorithm was upgraded by using a comprehensive rotorcraft analysis program, CAMRAD II. The presently improved conceptual design and optimization framework was validated using data of the XH-59A aircraft.

Hybrid Multi-layer Perceptron with Fuzzy Set-based PNs with the Aid of Symbolic Coding Genetic Algorithms

  • Roh, Seok-Beom;Oh, Sung-Kwun;Ahn, Tae-Chon
    • Proceedings of the KIEE Conference
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    • 2005.10b
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    • pp.155-157
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    • 2005
  • We propose a new category of hybrid multi-layer neural networks with hetero nodes such as Fuzzy Set based Polynomial Neurons (FSPNs) and Polynomial Neurons (PNs). These networks are based on a genetically optimized multi-layer perceptron. We develop a comprehensive design methodology involving mechanisms of genetic optimization and genetic algorithms, in particular. The augmented genetically optimized HFPNN (namely gHFPNN) results in a structurally optimized structure and comes with a higher level of flexibility in comparison to the one we encounter in the conventional HFPNN. The GA-based design procedure being applied at each layer of HFPNN leads to the selection of preferred nodes (FPNs or PNs) available within the HFPNN. In the sequel, two general optimization mechanisms are explored. First, the structural optimization is realized via GAs whereas the ensuing detailed parametric optimization is carried out in the setting of a standard least square method-based learning. The performance of the gHFPNNs quantified through experimentation where we use a number of modeling benchmarks-synthetic and experimental data already experimented with in fuzzy or neurofuzzy modeling.

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Comprehensive studies of Grassmann manifold optimization and sequential candidate set algorithm in a principal fitted component model

  • Chaeyoung, Lee;Jae Keun, Yoo
    • Communications for Statistical Applications and Methods
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    • v.29 no.6
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    • pp.721-733
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    • 2022
  • In this paper we compare parameter estimation by Grassmann manifold optimization and sequential candidate set algorithm in a structured principal fitted component (PFC) model. The structured PFC model extends the form of the covariance matrix of a random error to relieve the limits that occur due to too simple form of the matrix. However, unlike other PFC models, structured PFC model does not have a closed form for parameter estimation in dimension reduction which signals the need of numerical computation. The numerical computation can be done through Grassmann manifold optimization and sequential candidate set algorithm. We conducted numerical studies to compare the two methods by computing the results of sequential dimension testing and trace correlation values where we can compare the performance in determining dimension and estimating the basis. We could conclude that Grassmann manifold optimization outperforms sequential candidate set algorithm in dimension determination, while sequential candidate set algorithm is better in basis estimation when conducting dimension reduction. We also applied the methods in real data which derived the same result.

Optimal Supersonic Air-Launching Rocket Design Using Multidisciplinary System Optimization Approach (다분야 최적화 기법을 이용한 공중발사로켓 최적설계)

  • Choi Young Chang;Lee Jae-Woo;Byun Yung-Hwan
    • Proceedings of the Korean Society of Propulsion Engineers Conference
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    • v.y2005m4
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    • pp.11-15
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    • 2005
  • Compared with the conventional ground rocket launching, air-launching has many advantages. However, comprehensive and integrated system design approach is required because the physical geometry of air launch vehicle is quite dependent on the installation limitation of the mother plane. The system design has been performed using two different approaches: the sequential optimization and the multidisciplinary feasible(MDF) optimization method. Analysis modules include mission analysis, staging, propulsion analysis, configuration, weight analysis, aerodynamics analysis and trajectory analysis. MDF optimization shows better result than sequential optimization. As a result of system optimization, a supersonic air launching rocket with total mass of 1244.91 kg, total length of 6.18 m, outer diameter of 0.60 m and the payload mass of 7.5 kg has been successfully designed.

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Conceptual Design Optimization of Tensairity Girder Using Variable Complexity Modeling Method

  • Yin, Shi;Zhu, Ming;Liang, Haoquan;Zhao, Da
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.1
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    • pp.29-36
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    • 2016
  • Tensairity girder is a light weight inflatable fabric structural concept which can be used in road emergency transportation. It uses low pressure air to stabilize compression elements against buckling. With the purpose of obtaining the comprehensive target of minimum deflection and weight under ultimate load, the cross-section and the inner pressure of tensairity girder was optimized in this paper. The Variable Complexity Modeling (VCM) method was used in this paper combining the Kriging approximate method with the Finite Element Analysis (FEA) method, which was implemented by ABAQUS. In the Kriging method, the sample points of the surrogate model were outlined by Design of Experiment (DOE) technique based on Optimal Latin Hypercube. The optimization framework was constructed in iSIGHT with a global optimization method, Multi-Island Genetic Algorithm (MIGA), followed by a local optimization method, Sequential Quadratic Program (SQP). The result of the optimization gives a prominent conceptual design of the tensairity girder, which approves the solution architecture of VCM is feasible and efficient. Furthermore, a useful trend of sensitivity between optimization variables and responses was performed to guide future design. It was proved that the inner pressure is the key parameter to balance the maximum Von Mises stress and deflection on tensairity girder, and the parameters of cross section impact the mass of tensairity girder obviously.

Optimal Supersonic Air-Launching Rocket Design Using Multidisciplinary System Optimization Approach (다분야 최적화 기법을 이용한 공중발사 로켓 최적설계)

  • Choi, Young-Chang;Lee, Jae-Woo;ByUn, Yung-Hwan
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.33 no.12
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    • pp.26-32
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    • 2005
  • Compared with the conventional ground rocket launching, air-launching has many advantages. However, a comprehensive and integrated system design approach is required because the physical geometry of air launch vehicle is quite dependent on the installation limitation of the mother plane. The system design has been performed using two different approaches: the sequential optimization and the multidisciplinary feasible(MDF) optimization method. Analysis modules include mission analysis, staging, propulsion analysis, configuration, weight analysis, aerodynamics analysis and trajectory analysis. MDF optimization shows better results than the sequential optimization. As a result of system optimization, a supersonic air launching rocket with total mass of 1244.91kg, total length of 6.36m, outer diameter of 0.60m and the payload mass of 7.5kg has been successfully designed.

A Survey of Self-optimization Approaches for HetNets

  • Chai, Xiaomeng;Xu, Xu;Zhang, Zhongshan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.9 no.6
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    • pp.1979-1995
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    • 2015
  • Network convergence is regarded as the development tendency of the future wireless networks, for which self-organization paradigms provide a promising solution to alleviate the upgrading capital expenditures (CAPEX) and operating expenditures (OPEX). Self-optimization, as a critical functionality of self-organization, employs a decentralized paradigm to dynamically adapt the varying environmental circumstances while without relying on centralized control or human intervention. In this paper, we present comprehensive surveys of heterogeneous networks (HetNets) and investigate the enhanced self-optimization models. Self-optimization approaches such as dynamic mobile access network selection, spectrum resource allocation and power control for HetNets, etc., are surveyed and compared, with possible methodologies to achieve self-optimization summarized. We hope this survey paper can provide the insight and the roadmap for future research efforts in the self-optimization of convergence networks.